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Measuring Retiming Responses of Passengers to a Prepeak Discount Fare by Tracing Smart Card Data: A Practical Experiment in the Beijing Subway

机译:通过跟踪智能卡数据来衡量乘客对Prepeak折扣票价的回报响应:北京地铁的实践实验

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摘要

Understanding passengers' responses to fare changes is the basis to design reasonable price policies. This work aims to explore retiming responses of travelers changing departure times due to a prepeak discount pricing strategy in the Beijing subway in China, using smart card records from an automatic fare collection (AFC) system. First, a new set of classification indicators is established to segment passengers through a two-step clustering approach. Then, the potentially influenced passengers for the fare policy are identified, and the shifted passengers who changed their departure time are detected by tracing changes in passengers' expected departure times before and after the policy. Lastly, the fare elasticity of departure time is defined to measure the retiming responses of passengers. Two scenarios are studied of one month (short term) and six months (middle term) after the policy. The retiming elasticity of different passenger groups, retiming elasticity over time, and retiming elasticity functions of shifted time are measured. The results show that there are considerable differences in the retiming elasticities of different passenger groups; low-frequency passengers are more sensitive to discount fares than high-frequency passengers. The retiming elasticity decreases greatly with increasing shifted time, and 30 minutes is almost the maximum acceptable shifted time for passengers. Moreover, the retiming elasticity of passengers in the middle term is approximately twice that in the short term. Applications of fare optimization are also executed, and the results suggest that optimizing the valid time window of the discount fares is a feasible way to improve the congestion relief effect of the policy, while policy makers should be cautious to change fare structures and increase discounts.
机译:了解乘客对票价变化的回应是设计合理的价格政策的基础。这项工作旨在探讨旅行者因中国北京地铁的折扣定价策略而改变出发时间的回升响应,采用自动票价收集(AFC)系统的智能卡记录。首先,通过两步聚类方法建立新的分类指标,以便分段乘客。然后,确定了票价政策的潜在影响的乘客,并通过在政策前后的乘客预期的离境时间的变化来检测改变其出发时间的移位乘客。最后,出发时间的票价弹性被定义为衡量乘客的回升响应。在政策后,研究了两个场景,一个月(短期)和六个月(中期)。测量不同乘客群,重度弹性随时间的重度弹性,并测量移位时间的重度弹性功能。结果表明,不同乘客群体的重度弹性有相当大的差异;低频乘客对折扣票价比高频乘客更敏感。随着偏移时间的增加,重度弹性大大降低,30分钟几乎是乘客的最大可接受的移位时间。此外,中期乘客的重度弹性大约是短期内的两倍。还执行了票价优化的应用,结果表明,优化折扣票价的有效时间窗口是一种可行的方式,可以提高政策的拥堵救济效果,而政策制定者应该谨慎地改变票价结构和增加折扣。

著录项

  • 来源
    《Journal of Advanced Transportation》 |2019年第3期|6873912.1-6873912.20|共20页
  • 作者单位

    Shijiazhuang Tiedao Univ Sch Traff & Transportat Shijiazhuang 050043 Hebei Peoples R China|Beijing Jiaotong Univ Sch Traff & Transportat 3 Shangyuancun Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat 3 Shangyuancun Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat 3 Shangyuancun Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Civil Engn 3 Shangyuancun Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Civil Engn 3 Shangyuancun Beijing 100044 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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